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Museum specimens and citizen science initiatives are valuable sources of information on how anthropogenic activities affect biodiversity and how species respond to rapid global change. Although tropical regions harbor most of the planet’s biodiversity, investigations on species’ phenological changes are heavily biased towards temperate regions. Such unevenness in phenological research is also taxonomically biased, with reptiles being the least studied group among tetrapod species regarding animal phenology. Herein we used long-term time series data to investigate environmentally driven changes in the activity pattern of tropical forest snakes. We gathered natural history collection and citizen science data for 25 snake species (five venomous and 20 non-venomous) from an Atlantic Forest region in southeastern Brazil. Using circular mixed-effects models, we investigate whether snake activity patterns followed the variation in environmental variables over a decade. Our results show that the activity pattern of Atlantic Forest snakes was seasonal and largely driven by average temperature and relative humidity. Since snakes are ectothermic animals, they are particularly sensitive to temperature variations, especially at small scales. Moreover, relative humidity can affect snake seasonal activities through physiological constraints and/or prey availability. Most specimens were registered during the rainy season, with highly venomous snakes (lanceheads and coral snakes) emerging as the most abundant taxa. We highlight the importance of citizen science and natural history collections in better understanding biodiversity. Furthermore, our data obtained from local collectors underscores the need environmental education programs and collaboration between researchers and local decision-makers to raise awareness and reduce conflicts between people and snakes in the region. Methods All analyses in this study were performed in the software R v. 4.0.2. Raw data and R-code to replicate the findings of this study are as follow: 1. Rscript_SnakeSeasonalActivity.R 2.rawdata.csv 3.INMET_SE_MG_A510_VICOSA_2009_2018.csv 4.SnakeBiteData.csv The R-script is commented by the authorsand contains all code used to analyze data tables, get summary stats, perform the models,and create the figures in the manuscript. Acknowledgements We thank the environmental police officers, firefighters, security guards, and other local collectors who brought snakes to MZUFV along the years. JJMG is supported by a PhD scholarship from Coordenacão de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). MRM acknowledges support from São Paulo Research Foundation (FAPESP) for grants proc. 2021/11840-6 and proc. 2022/12231-6.

This review assesses the potential applications of alkali-activated silico-manganese slag (SiMnS). It covers three main sections: (i) the characteristics of SiMnS, (ii) its use as an alkali-activated precursor, and (iii) environmental perspectives. SiMnS shows promise as an alkali-activated material with diverse applications in civil construction. Future prospects include their use in heavy metal immobilization, understanding rheological behavior for effective admixture development, and utilization of one-part mix systems with alternative activators. Overall, the use of SiMnS as a precursor for alkali activation contributes to waste reduction and provides many environmental and economic benefits. Methods This study aims to review existing literature on the use of SiMnS in alkali-activated material. The R-codeis commented by the authorsand contains all steps necessaryto createsome of thefigures presented in the manuscript. The R version used was 4.0.2. 1. Rcode.R 2.raw_data.xlsx 3.ternary_data.xlsx 4.IncludedPapers.bib Acknowledgements We gratefully acknowledge the Federal University of Ouro Preto, and the agencies CAPES, CNPq, and FAPEMIG.

More than two million species have been described so far, but our knowledge on most taxa remains scarce or inexistent, and the available biodiversity data is often taxonomically, phylogenetically, and spatially biased. Unevenness in research effort across species or regions can interact with data biases and compromise our ability to properly study and conserve biodiversity. Herein, we assess the influence of biological, conservation, geographic, and socioeconomic correlates of reptile research effort globally and across six biogeographic realms. We combine bibliometric data from the Scopus database with trait-based approaches and provide research effort information for 10,531 reptile species, modelling it as a function of 10 putative correlates of species-level variation in research effort through negative binomial generalised mixed effect models. We show that reptile research effort is highly skewed toward certain taxa and regions, such as turtles, crocodiles, tuatara, viperids, pythons, and some anguimorph lizards, as well as for temperate compared to tropical regions. Our findings indicate that greater research attention is directed towards large-sized and early described reptile species, particularly those whose geographic range overlap with biodiversity institutions. Although we demonstrate that biological and socioeconomic factors more strongly affect reptile research effort variation, geography and conservation-related factors also matter. Global patterns are mostly consistent, but variation across realms were observed and likely reflects differences in socioeconomic attributes as well as in the amount of species to be studied in each realm. Directing researchers and citizen scientists’ attention toward understudied taxa will contribute to alleviate this biased biodiversity knowledge, although the sheer amount of species in tropical regions inevitably makes it a long-term solution. Performing comparative studies across species with similar levels of research attention could represent a more immediate and feasible alternative. Methods All analyses in this study were performed in the software R v. 4.0.2. Raw data and R-code to replicate the findings of this study are as follow: 1. Guedesetal_ReptileResearchEffort.R 2.ResearchEffortData.csv 3.ReptSpatialData.csv 4.Subset100Supertrees_7102taxaReptiles.Rdata 5.gridcells_110km.zip The R-script (the second version)is commented by the authorsand contains all code used to analyze data tablesand create the figures in the manuscript. Acknowledgements This study was financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001, as a D.Sc. scholarship provided to JJMG. Work by J.A.F.D.-F. is supported by CNPq productivity fellowships and has been developed associated with the National Institutes for Science and Technology (INCT) in Ecology, Evolution and Biodiversity Conservation, supported by MCTIC/CNPq (proc. 465610/2014-5) and FAPEG (proc. 201810267000023).